Improve example testing

cpmpy/solvers/utils.py

@@ -160,7 +160,7 @@ def lookup(cls, name=None):
             if basename == solvername:
                 # found the right solver
                 return CPM_slv
-        raise ValueError(f"Unknown solver '{name}', chose from {cls.solvernames()}")
+        raise ValueError(f"Unknown solver '{name}', choose from {cls.solvernames()}")
 
 
 # using `builtin_solvers` is DEPRECATED, use `SolverLookup` object instead

examples/advanced/counterfactual_explain.py

@@ -210,7 +210,11 @@ def inverse_optimize(values, weights, capacity, x_d, foil_idx):
         if sum(d_star * x_d) >= sum(d_star * x_0.value()):
             return d_star
         else:
-            master_model += [sum(d * x_d) >= sum(d * x_0.value())]
+            # Convert boolean arrays to integer arrays
+            x_d_int = x_d.astype(int)
+            x_0_val_int = x_0.value().astype(int)
+            # Add constraint using integer coefficients
+            master_model += [sum(d * x_d_int) >= sum(d * x_0_val_int)]
         i += 1
 
     raise ValueError("Master model is UNSAT!")

examples/advanced/ocus_explanations.py

@@ -55,10 +55,9 @@ def explain_ocus(soft, soft_weights=None,  hard=[], solver="ortools", verbose=0)
     # compute all derivable literals
     full_sol = solution_intersection(Model(hard + soft), solver, verbose)
 
-
     # prep soft constraint formulation with a literal for each soft constraint
     # (so we can iteratively use an assumption solver on softliterals)
-    soft_lit = BoolVar(shape=len(soft), name="ind")
+    soft_lit = boolvar(shape=len(soft), name="ind")
     reified_soft = []
     for i,bv in enumerate(soft_lit):
         reified_soft += [bv.implies(soft[i])]
@@ -196,7 +195,7 @@ def explain_one_step_ocus(hard, soft_lit, cost, remaining_sol_to_explain, solver
     ## ----- SAT solver model ----
     SAT = SolverLookup.lookup(solver)(Model(hard))
 
-    while(True):
+    while True:
         hittingset_solver.solve()
 
         # Get hitting set
@@ -209,7 +208,7 @@ def explain_one_step_ocus(hard, soft_lit, cost, remaining_sol_to_explain, solver
             print("\n\t hs =", hs, S)
 
         # SAT check and computation of model
-        if not SAT.solve(assumptions=S):
+        if not SAT.solve(assumptions=list(S)):
             if verbose > 1:
                 print("\n\t ===> OCUS =", S)
 
@@ -242,7 +241,7 @@ def solution_intersection(model, solver="ortools", verbose=False):
     assert SAT.solve(), "Propagation of soft constraints only possible if model is SAT."
     sat_model = set(bv if bv.value() else ~bv for bv in sat_vars)
 
-    while(SAT.solve()):
+    while SAT.solve():
         # negate the values of the model
         sat_model &= set(bv if bv.value() else ~bv for bv in sat_vars)
         blocking_clause = ~all(sat_model)
@@ -265,11 +264,10 @@ def cost_func(soft, soft_weights):
     '''
 
     def cost_lit(cons):
-        # return soft weight if constraint is a soft constraint
-        if len(set({cons}) & set(soft)) > 0:
+        # return soft weight if the constraint is a soft constraint
+        if len({cons} & set(soft)) > 0:
             return soft_weights[soft.index(cons)]
-        else:
-            return 1
+        return 1
 
     return cost_lit
 

examples/csplib/prob007_all_interval.py

@@ -60,14 +60,14 @@ def print_solution(x, diffs):
 
     parser = argparse.ArgumentParser(description=__doc__)
     parser.add_argument("-length", type=int,help="Length of array, 12 by default", default=12)
-    parser.add_argument("--solution_limit", type=int, help="Number of solutions to find, find all by default", default=0)
+    parser.add_argument("--solution_limit", type=int, help="Number of solutions to find, find all by default", default=10)
 
     args = parser.parse_args()
 
     model, (x, diffs) = all_interval(args.length)
     found_n = model.solveAll(solution_limit=args.solution_limit,
                              display=lambda: print_solution(x, diffs))
-    if found_n == 0:
-        print(f"Fund {found_n} solutions")
+    if found_n > 0:
+        print(f"Found {found_n} solutions")
     else:
         raise ValueError("Problem is unsatisfiable")

examples/csplib/prob011_basketball_schedule.py

@@ -116,20 +116,25 @@ def basketball_schedule():
         for d in days[:-2]:
             if t != DUKE and t != UNC:
                 # No team plays in two consecutive dates away against UNC and Duke
-                model += ~((config[d, t] == UNC) & (where[d,t] == AWAY) &
-                           (config[d+1, t] == DUKE) & (where[d+1,t] == AWAY))
-                model += ~((config[d, t] == DUKE) & (where[d,t] == AWAY) &
-                           (config[d+1, t] == UNC) & (where[d+1,t] == AWAY))
+                model += ((config[d, t] == UNC) & (where[d, t] == AWAY) &
+                          (config[d + 1, t] == DUKE) & (where[d + 1, t] == AWAY)).implies(False)
+                model += ((config[d, t] == DUKE) & (where[d, t] == AWAY) &
+                          (config[d + 1, t] == UNC) & (where[d + 1, t] == AWAY)).implies(False)
         for d in days[:-3]:
             if t not in [UNC, DUKE, WAKE]:
                 # No team plays in three consecutive dates against UNC, Duke and Wake (independent of home/away).
-                model += ~((config[d,t] == UNC)  & (config[d+1,t] == DUKE) & (config[d+2] == WAKE))
-                model += ~((config[d,t] == UNC)  & (config[d+1,t] == WAKE) & (config[d+2] == DUKE))
-                model += ~((config[d,t] == DUKE) & (config[d+1,t] == UNC)  & (config[d+2] == WAKE))
-                model += ~((config[d,t] == DUKE) & (config[d+1,t] == WAKE) & (config[d+2] == UNC))
-                model += ~((config[d,t] == WAKE) & (config[d+1,t] == UNC)  & (config[d+2] == DUKE))
-                model += ~((config[d,t] == WAKE) & (config[d+1,t] == DUKE) & (config[d+2] == UNC))
-
+                model += ((config[d, t] == UNC) & (config[d + 1, t] == DUKE) & (config[d + 2, t] == WAKE)).implies(
+                    False)
+                model += ((config[d, t] == UNC) & (config[d + 1, t] == WAKE) & (config[d + 2, t] == DUKE)).implies(
+                    False)
+                model += ((config[d, t] == DUKE) & (config[d + 1, t] == UNC) & (config[d + 2, t] == WAKE)).implies(
+                    False)
+                model += ((config[d, t] == DUKE) & (config[d + 1, t] == WAKE) & (config[d + 2, t] == UNC)).implies(
+                    False)
+                model += ((config[d, t] == WAKE) & (config[d + 1, t] == UNC) & (config[d + 2, t] == DUKE)).implies(
+                    False)
+                model += ((config[d, t] == WAKE) & (config[d + 1, t] == DUKE) & (config[d + 2, t] == UNC)).implies(
+                    False)
 
     # 9. Other constraints
     # UNC plays its rival Duke in the last date and in date 11

examples/csplib/prob013_progressive_party.py

@@ -23,39 +23,36 @@
 
 
 def progressive_party(n_boats, n_periods, capacity, crew_size, **kwargs):
-
     is_host = boolvar(shape=n_boats, name="is_host")
-    visits = intvar(lb=0, ub=n_boats-1, shape=(n_periods,n_boats), name="visits")
+    visits = intvar(0, n_boats - 1, shape=(n_periods, n_boats), name="visits")
 
     model = Model()
 
-    # crews of host boats stay on boat
+    # Crews of host boats stay on boat
     for boat in range(n_boats):
-        model += (is_host[boat]).implies(all(visits[:,boat] == boat))
+        model += (is_host[boat]).implies((visits[:, boat] == boat).all())
 
-    # number of visitors can never exceed capacity of boat
+    # Number of visitors can never exceed capacity of boat
     for slot in range(n_periods):
         for boat in range(n_boats):
-            model += sum((visits[slot] == boat) * crew_size) <= capacity[boat]
+            model += sum((visits[slot] == boat) * crew_size) + crew_size[boat] * is_host[boat] <= capacity[boat]
 
-    # guests cannot visit a boat twice
+    # Guests cannot visit a boat twice
     for boat in range(n_boats):
-        # Alldiff must be decomposed in v0.9.8, see issue #105 on github
-        model += (~is_host[boat]).implies(all((AllDifferent(visits[:,boat]).decompose())))
+        model += (~is_host[boat]).implies(AllDifferent(visits[:, boat]))
 
-    # non-host boats cannot be visited
+    # Non-host boats cannot be visited
     for boat in range(n_boats):
-        model += (~is_host[boat]).implies(all(visits != boat))
+        model += (~is_host[boat]).implies((visits != boat).all())
 
-    # crews cannot meet more than once
+    # Crews cannot meet more than once
     for c1, c2 in all_pairs(range(n_boats)):
-        model += sum(visits[:,c1] == visits[:,c2]) <= 1
+        model += sum(visits[:, c1] == visits[:, c2]) <= 1
 
-    # minimize number of hosts needed
+    # Minimize number of hosts needed
     model.minimize(sum(is_host))
 
-    return model, (visits,is_host)
-
+    return model, (visits, is_host)
 
 
 # Helper functions
@@ -79,7 +76,7 @@ def _print_instances(data):
     # argument parsing
     url = "https://raw.githubusercontent.com/CPMpy/cpmpy/csplib/examples/csplib/prob013_progressive_party.json"
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
-    parser.add_argument('-instance', nargs='?', default="csplib_example", help="Name of the problem instance found in file 'filename'")
+    parser.add_argument('-instance', nargs='?', default="lan01", help="Name of the problem instance found in file 'filename'")
     parser.add_argument('-filename', nargs='?', default=url, help="File containing problem instances, can be local file or url")
     parser.add_argument('--list-instances', help='List all problem instances', action='store_true')
 

examples/csplib/prob024_langford.py

@@ -62,7 +62,7 @@ def print_solution(position, solution):
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
     parser.add_argument("-k", type=int, default=8, help="Number of integers")
-    parser.add_argument("--solution_limit", type=int, default=0, help="Number of solutions to search for, find all by default")
+    parser.add_argument("--solution_limit", type=int, default=10, help="Number of solutions to search for, find all by default")
 
     args = parser.parse_args()
 

examples/csplib/prob026_sport_scheduling.py

@@ -46,7 +46,7 @@ def sport_scheduling(n_teams):
     import argparse
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
-    parser.add_argument("-n_teams", type=int, default=8, help="Number of teams to schedule")
+    parser.add_argument("-n_teams", type=int, default=6, help="Number of teams to schedule")
 
     args = parser.parse_args()
 

examples/csplib/prob028_bibd.py

@@ -58,7 +58,7 @@ def bibd(v, b, r, k, l):
     import argparse
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
-    parser.add_argument("--solution_limit", type=int, default=0, help="Number of solutions to find, find all by default")
+    parser.add_argument("--solution_limit", type=int, default=10, help="Number of solutions to find, find all by default")
 
     args = parser.parse_args()
 
@@ -73,4 +73,4 @@ def bibd(v, b, r, k, l):
     if num_solutions == 0:
         raise ValueError("Model is unsatisfiable")
     else:
-        print(f"Found {num_solutions} solutions")
+        print(f"Found {num_solutions} solutions")

examples/csplib/prob033_word_design.py

@@ -56,7 +56,7 @@ def word_design(n=2):
     import argparse
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
-    parser.add_argument("-n_words", type=int, default=24, help="Number of words to find")
+    parser.add_argument("-n_words", type=int, default=8, help="Number of words to find")
 
     n = parser.parse_args().n_words
 

examples/csplib/prob044_steiner.py

@@ -55,7 +55,7 @@ def print_sol(sets):
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
     parser.add_argument("-num_sets", type=int, default=15, help="Number of sets")
-    parser.add_argument("--solution_limit", type=int, default=0, help="Number of solutions to find, find all by default")
+    parser.add_argument("--solution_limit", type=int, default=10, help="Number of solutions to find, find all by default")
 
     args = parser.parse_args()
 
@@ -67,4 +67,4 @@ def print_sol(sets):
     if n_sol == 0:
         raise ValueError("Model is unsatisfiable")
     else:
-        print(f"Found {n_sol} solutions")
+        print(f"Found {n_sol} solutions")

examples/csplib/prob050_diamond_free.py

@@ -84,7 +84,7 @@ def print_sol(matrix):
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
     parser.add_argument("-n", type=int, default=10, help="Size of diamond")
-    parser.add_argument("--solution-limit", type=int, default=0, help="Number of solutions to find, find all by default")
+    parser.add_argument("--solution-limit", type=int, default=10, help="Number of solutions to find, find all by default")
 
     args = parser.parse_args()
 

examples/csplib/prob054_n_queens.py

@@ -47,7 +47,7 @@ def print_sol(queens):
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
     parser.add_argument("-n", type=int, default=16, help="Number of queens")
-    parser.add_argument("--solution_limit", type=int, default=0, help="Number of solutions, find all by default")
+    parser.add_argument("--solution_limit", type=int, default=10, help="Number of solutions, find all by default")
 
     args = parser.parse_args()
 

examples/csplib/prob076_costas_arrays.py

@@ -82,7 +82,7 @@ def print_sol(costas, differences):
 
     parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
     parser.add_argument("-size", type=int, default=6, help="Size of array")
-    parser.add_argument("--solution_limit", type=int, default=0, help="Number of solutions, find all by default")
+    parser.add_argument("--solution_limit", type=int, default=10, help="Number of solutions, find all by default")
 
     args = parser.parse_args()
 

examples/flexible_jobshop.py

@@ -66,10 +66,17 @@
     print("No solution found.")
 
 
+def compare_solvers(model):
+    """
+    Compare the runtime of all installed solvers on the given model.
+    """
+    print("Solving with all installed solvers...")
+    for solvername in cp.SolverLookup.solvernames():
+        try:
+            model.solve(solver=solvername, time_limit=10)  # max 10 seconds
+            print(f"{solvername}: {model.status()}")
+        except Exception as e:
+            print(f"{solvername}: Not run -- {str(e)}")
+
 # --- bonus: compare the runtime of all installed solvers ---
-for solvername in cp.SolverLookup.solvernames():
-    try:
-        model.solve(solver=solvername, time_limit=10)  # max 10 seconds
-        print(f"{solvername}: {model.status()}")
-    except Exception as e:
-        print(f"{solvername}: Not run -- {str(e)}")
+# compare_solvers(model)

setup.py

@@ -52,7 +52,7 @@ def get_version(rel_path):
         # Tools
         # "xcsp3": ["pycsp3"], <- for when xcsp3 is merged
         # Other
-        "test": ["pytest"],
+        "test": ["pytest", "pytest-timeout"],
         "docs": ["sphinx>=5.3.0", "sphinx_rtd_theme>=2.0.0", "myst_parser", "sphinx-automodapi", "readthedocs-sphinx-search>=0.3.2"],
     },
     classifiers=[